U.S. patent application number 14/201769 was filed with the patent office on 2014-09-11 for methods and systems for analyzing and reporting medical images.
This patent application is currently assigned to Radlogics, Inc.. The applicant listed for this patent is Radlogics, Inc.. Invention is credited to Moshe Becker, Robert M. Foley, Eliahu Konen, Arnaldo Mayer.
Application Number | 20140257854 14/201769 |
Document ID | / |
Family ID | 47832793 |
Filed Date | 2014-09-11 |
United States Patent
Application |
20140257854 |
Kind Code |
A1 |
Becker; Moshe ; et
al. |
September 11, 2014 |
Methods and Systems for Analyzing and Reporting Medical Images
Abstract
A method for providing medical diagnostics comprises providing
access to one or more platforms capable of distributing one or more
applications for implementing a method. The method comprises
retrieving, with the aid of a processor, one or more images from an
image database or an imaging device. The one or more images can
define a set of images. Next, with the aid of a processor, whether
each of the images is of medical interest to a reviewing physician
is determined. One or more images can then be provided to a display
and analysis system for review by a reviewing physician. The one or
more images can be provided with an image that is representative of
the set of images.
Inventors: |
Becker; Moshe; (Los Gatos,
CA) ; Foley; Robert M.; (Palo Alto, CA) ;
Konen; Eliahu; (Tel-Aviv, IL) ; Mayer; Arnaldo;
(Herzeliya, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Radlogics, Inc. |
Los Gatos |
CA |
US |
|
|
Assignee: |
Radlogics, Inc.
Los Gatos
CA
|
Family ID: |
47832793 |
Appl. No.: |
14/201769 |
Filed: |
March 7, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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PCT/US2012/054272 |
Sep 7, 2012 |
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14201769 |
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61532514 |
Sep 8, 2011 |
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61532515 |
Sep 8, 2011 |
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61532519 |
Sep 8, 2011 |
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61532540 |
Sep 8, 2011 |
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Current U.S.
Class: |
705/3 |
Current CPC
Class: |
G06F 16/50 20190101;
G16H 30/20 20180101; G16H 15/00 20180101; G16H 50/20 20180101 |
Class at
Publication: |
705/3 |
International
Class: |
G06F 19/00 20060101
G06F019/00; G06F 17/30 20060101 G06F017/30; G06Q 50/24 20060101
G06Q050/24 |
Claims
1. A method for providing medical diagnostic images, comprising:
(a) retrieving, with the aid of a processor, one or more images
from an image database or an imaging device, the one or more images
defining a set of images; (b) selecting, with the aid of a
processor, one or more images from the set of images based on
diagnostic data stored within a memory; (c) generating a report
including the one or more selected images and providing the report
to a reviewing physician; (d) receiving one or more modifications
to the report from the reviewing physician; and (e) updating the
diagnostic data based on the one or more modifications.
2. (canceled)
3. The method of claim 1 wherein the diagnostic data is stored in a
diagnostic table, and updating diagnostic data includes updating
the diagnostic table.
4. The method of claim 1 further comprising: retrieving, with the
aid of a processor, one or more additional images; defining an
additional set of images; and selecting one or more images from the
additional set of images based on the updated diagnostic data.
5. A method for providing medical diagnostic images, comprising:
(a) retrieving, with the aid of a processor, one or more images
from an image database or an imaging device, the one or more images
defining a set of images; (b) selecting one or more images from the
set of images based on diagnostic data stored within a memory; (c)
generating a report including the one or more selected images; (d)
providing the report to a reviewing physician; (e) receiving
subject outcome information relating to subject responsiveness to
treatment; and (f) updating the diagnostic data based on the
subject outcome information.
6. The method of claim 5, wherein said one or more images are
retrieved from said image database.
7. The method of claim 5 further comprising receiving a clinical
diagnosis for a subject, wherein said subject is associated with
the set of images; receiving initial radiological findings for said
subject; retrieving one or more images multiple times during
treatment of said subject; and determining whether the initial
radiological findings were supported.
8. The method of claim 7, further comprising updating the
diagnostic data with discrepancy-related information if the initial
radiological findings were not supported.
9. The method of claim 8, further comprising: receiving one or more
modifications to the report from the reviewing physician; and
updating the diagnostic data based on the modification.
10. (canceled)
11. (canceled)
12. (canceled)
13. A method for providing medical diagnostic images, comprising:
(a) retrieving, with the aid of a processor, one or more images
from an image database or an imaging device, the one or more images
defining a set of images; (b) retrieving, one or more boundary
parameters from a memory location coupled to said processor; (c)
determining whether each of the images falls within said boundary
parameters; and (d) providing one or more alerts for an urgent
medical condition if, based on said determining of (c), a given
image among said one or more of images falls within the boundary
parameters.
14. The method of claim 13, wherein the one or more alerts provide
a request for an immediate emergency response.
15. The method of claim 13, wherein a reviewing physician is urged
to review the validity of the urgent medical condition
immediately.
16. The method of claim 15, wherein an additional reviewing
physician is urged to review the information.
17. The method of claim 16, wherein at least one of the reviewing
physician and the additional reviewing physician is a
radiologist.
18. The method of claim 16, wherein the additional reviewing
physician is offsite.
19. The method of claim 13, further comprising providing additional
information for assessing the medical condition from one or more
databases.
20. The method of claim 13, further comprising providing a decision
support system, wherein additional clinical findings are reviewed
to determine whether said one or more alerts should have been
provided or not.
21. The method of claim 13, wherein the one or more images
highlight image features that led to the raising of the alert.
22. The method of claim 13, wherein the alert is an automatic phone
call, SMS text message, pager alert, or email to a radiologist on
duty and/or a referring physician.
23. The method of claim 13, wherein the alert includes a copy of
one or more representative images and/or a description of boundary
parameters.
24. The method of claim 13, further comprising analyzing, with the
aid of a processor, a condition of a subject based on the images,
and designating a case priority based on the analysis.
25. The method of claim 24, wherein the case priority includes a
designation of a high, medium, or low priority.
26. The method of claim 24, further comprising prioritizing a
plurality of cases.
27. (canceled)
28. (canceled)
29. (canceled)
30. (canceled)
31. (canceled)
32. A method for providing subject medical diagnostic images,
comprising: (a) retrieving, with the aid of processor, one or more
images associated with a subject from an image database or an
imaging device, the one or more images defining a set of images;
(b) retrieving, historical data of said subject from a memory
location; (c) comparing, with the aid of a processor, the one or
more images with the historical data; and (d) providing the one or
more images and the historical data to a reviewing physician.
33. The method of claim 32, further comprising determining whether
each of the one or more images is of medical interest to the
reviewing physician.
34. The method of claim 32, wherein the historical data includes
one or more historical images associated with said subject.
35. The method of claim 32, further comprising retrieving data from
one or more additional information source.
36. The method of claim 35, wherein the one or more additional
information source includes one or more of the following: news
articles, or data from one or more additional subjects.
37. The method of claim 36, wherein the additional information is
provided to the reviewing physician.
38. The method of claim 36, wherein the additional information
and/or the historical data is used by a processor to analyze the
one or more images.
39. The method of claim 38, wherein said comparison is used to
detect one or more medical condition, and provide an alert if the
medical condition exceeds one or more boundary parameter.
40. The method of claim 36, wherein the one or more additional
subjects shares one or more peer group attribute with said
subject.
41. The method of claim 32, wherein the data provided to the
reviewing physician includes one or more of the following: volume,
attributes, measurements, statistics, examples from one or more
similar cases of an additional subject, and examples from one or
more articles.
42-56. (canceled)
Description
CROSS-REFERENCE
[0001] This application is a continuation of PCT/US2012/054272,
filed Sep. 7, 2012, which claims priority to U.S. Provisional
Patent Application Ser. No. 61/532,514, filed Sep. 8, 2011, U.S.
Provisional Patent Application Ser. No. 61/532,515, filed Sep. 8,
2011, U.S. Provisional Patent Application Ser. No. 61/532,519,
filed Sep. 8, 2011, and U.S. Provisional Patent Application Ser.
No. 61/532,540, filed Sep. 8, 2011, which applications are entirely
incorporated herein by reference.
BACKGROUND
[0002] Medical imaging systems, such as computerized tomography
("CT") scanners and magnetic resonance imaging ("MRI") scanners,
allow a physician to examine a patient's internal organs and areas
of the patient's body that require a thorough examination for
medical treatment. In use, a visualizing scanner outputs
two-dimensional ("2D") and three-dimensional ("3D") medical images
that can include a sequence of computerized cross-sectional images
of a certain body organ, which is then interpreted by reviewing
physician, such as a specialized radiologist.
[0003] Commonly, a patient is referred for a visual scan by a
general practitioner or an expert (or specialized) practitioner. A
series of 2D and sometimes 3D medical images (or scans) are
subsequently obtained. The scan is then forwarded to a reviewing
physician (such as a radiologist) who is responsible for the
analysis and diagnosis of the scan. Radiologists are typically
trained to analyze medical images from various parts of a patient's
body, such as medical images of the brain, abdomen, spine, chest,
pelvis and joints. After a radiologist (or other reviewing
physician) analyzes the medical images, he or she prepares a
document ("Radiology Report") that includes radiological findings,
and sometimes key images from the scan that best show the findings.
The radiology report is then sent back to the referring
practitioner.
[0004] In most hospitals and radiology centers, the scan is
transferred to a picture archiving communication system ("PACS")
before being accessed by the radiologists. A PACS is a computer
system that acquires, transmits, stores, retrieves, and displays
digital images and related subject (or patient) information from a
variety of imaging sources and communicates the information over a
network. Many hospitals are also equipped with a radiology
information system ("RIS")--used by radiology departments to
perform patient tracking and scheduling, result reporting and image
tracking. Medical images are typically stored in an independent
format, such as a Digital Imaging and Communications in Medicine
("DICOM") format. Electronic images and reports are transmitted
digitally via PACS, which eliminates the need to manually file,
retrieve or transport film jackets. A PACS typically includes four
components: the imaging modalities, such as computer axial
tomography ("CAT") or CT, MRI, position emission tomography
("PET"), or PET/CT; a secured network for the transmission of
patient information; workstations for interpreting and reviewing
images; and long and short term archives for the storage and
retrieval of images and reports.
[0005] There are image retrieval and processing systems and methods
available in the art. For example, U.S. patent application Ser. No.
12/178,560 to Yu ("Yu"), entitled "SYSTEMS FOR GENERATING RADIOLOGY
REPORTS," which is entirely incorporated herein by reference,
provides a method for generating a patient report, comprising
presenting an operator with an on screen menu of standardized types
of reports and having the operator select a standardized type of
report from the on screen menu of standardized types of reports.
The operator is presented with an on-screen organ list
corresponding to the selected standardized type of report. For each
organ, the operator is presented with a menu of standard medical
descriptions corresponding to the organ. The operator then
determines a medical description corresponding to each organ. Yu
furthe provides outputting a patient report describing the medical
description of each organ.
[0006] As another example, U.S. patent application Ser. No.
11/805,532 to Nekrich ("Nekrich"), entitled "RADIOLOGY CASE
DISTRIBUTION AND SORTING SYSTEMS AND METHODS," which is entirely
incorporated herein by reference, provides a system and method for
processing an image, including a means for receiving image
information, a means for queuing the image information, and a means
for receiving profile information for a plurality of image
analysts. The system of Nekrich can further include a means for
selecting an image analyst from the plurality of image analysts by
comparing the image information from the profile information.
[0007] As another example, U.S. patent application Ser. No.
12/224,652 to Bar-Aviv et al. ("Bar-Aviv"), entitled "SYSTEM AND
METHOD OF AUTOMATIC PRIORITIZATION AND ANALYSIS OF MEDICAL IMAGES,"
which is entirely incorporated herein by reference, teaches a
system for analyzing a source medical image of a body organ. The
system of Bar-Aviv comprises an input unit for obtaining the source
medical image having three dimensions or more, a feature extraction
unit that is designed for obtaining a number of features of the
body organ from the source medical image, and a classification unit
that is designed for estimating a priority level according to the
features.
[0008] While current medical image retrieval and processing systems
have provided physicians tremendous capabilities in storing and
retrieving medical images, there are limitations associated with
these systems. For instance, for a typical scan, a hospital may
obtain hundreds of images, and a reviewing physician might not have
time to review each of the images to determine whether a patient
has a particular type of medical condition. In cases in which a
hospital scans several patients in a relatively short period of
time, the hospital might not have the resources to timely review
each patient's (or subject's) medical images to determine whether a
physician should further review the image, and whether the patient
has a particular type of medical condition.
[0009] In addition, modern medical imaging systems can operate much
more quickly than older systems, which has led to a decrease in the
time it takes to generate a scan. While a shorter scan time could
be beneficial for providing rapid patient care, it has resulted in
an increase in the amount of data that must be compiled, analyzed
and presented to a reviewing physician. Modern medical imaging
systems can operate at higher resolutions, resulting in increased
number of higher resolution two-dimensional images and/or
three-dimensional images (or scans thereof). As the time to
generate scans decreases and the number of scans (and images
obtained) per patient increases, hospitals without sufficient
resources might not be able to review each image and provide
patients with medical care in an accurate and efficient manner.
Further, while some hospitals might have medical imaging,
processing and retrieval systems for handling scans, current
systems are not capable of accurately and efficiently prioritizing
scans. In addition, current systems do not provide scan reviewing
and patient treating physicians with the capability to acquire
accurate patient-specific diagnostic information from each of the
images or scans.
SUMMARY
[0010] This disclosure provides systems and methods for retrieving,
analyzing and presenting medical images to a physician or other
healthcare provider.
[0011] In an aspect of the invention, computer-implemented methods
for providing medical diagnostic images and enhanced report
capabilities are provided.
[0012] In an embodiment, a computer-implemented method for
providing medical diagnostic images comprises using a computer
system to retrieve one or more images from an image database or an
imaging device (e.g., imaging modality), the one or more images
defining a set of images; using the computer system to determine
whether each of the images is of medical interest to a reviewing
physician; using the computer system to determine whether one or
more of the images is representative of the set of images; and
providing the one or more images to a display and analysis system
for review by a reviewing physician, wherein the one or more images
are provided with an image that is representative of the set of
images.
[0013] In another embodiment, a computer-implemented method for
providing enhanced report capabilities for medical diagnostic
images comprises retrieving one or more images from an image
database or an imaging device, the one or more images defining a
set of images; determining whether each of the images is of medical
interest to a reviewing physician; determining whether one or more
of the images is representative of the set of images; providing the
one or more images to a display and analysis system for review by a
reviewing physician; and providing one or more text blocks
associated with items determined to be of medical interest, the one
or more text blocks for being mixed, matched and edited by a
reviewing physician to create a report.
[0014] In another aspect of the invention, a system for visualizing
and reporting patient-specific (or subject-specific) medical
information comprises an imaging modality for retrieving medical
diagnostic images from a patient (or subject); a reviewing system
for displaying medical images to a reviewing physician; a
prioritization visualization and reporting system in communication
with the imaging modality and the reviewing system, wherein the
prioritization visualization and reporting system is for retrieving
one or more images from the imaging modality, the one or more
images defining a set of images, determining whether each of the
images is of medical interest to a reviewing physician, determining
whether one or more of the images is representative of the set of
images and providing the one or more images to the reviewing
system, wherein the one or more images are provided with an image
that is representative of the set of images.
[0015] In another aspect, a method for providing medical diagnostic
images comprises retrieving, using a processor, one or more images
from an image database or an imaging device, the one or more images
defining a set of images; selecting one or more images from the set
of images based on diagnostic data stored within a memory;
generating a report including the one or more selected images and
providing the report to a reviewing physician; receiving one or
more modifications to the report from the reviewing physician; and
updating the diagnostic data based on the modification.
[0016] In an embodiment, a method for providing medical diagnostic
images comprises retrieving, using a processor, one or more images
from an image database or an imaging device, the one or more images
defining a set of images; selecting one or more images from the set
of images based on diagnostic data stored within a memory;
generating a report including the one or more selected images and
providing the report to a reviewing physician; receiving patient
outcome information relating to patient responsiveness to
treatment; and updating the diagnostic data based on the patient
outcome information.
[0017] In another aspect, a system for providing medical diagnostic
images comprises a database operatively coupled to an imaging
device, the database configured to store one or more images from
the imaging device, the one or more images defining a set of
images; and a processor configured to: generate a report from one
or more images selected from the set of images and provide the
report for review by a reviewing physician, wherein said one or
more images are selected based on diagnostic data stored in the
database; receive one or more modifications to the report from the
reviewing physician; and update the diagnostic data based on the
one or more modifications.
[0018] In another aspect, a method for providing medical diagnostic
images comprises retrieving, using a processor, one or more images
from an image database or an imaging device, the one or more images
defining a set of images; retrieving, one or more boundary
parameters from a memory; determining, using a processor, whether
each of the images is falls within the boundary parameters; and
providing one or more alert for an urgent medical condition if one
or more of the images falls within the boundary parameters.
[0019] In another aspect, a system for providing medical diagnostic
images comprises an imaging modality for retrieving medical
diagnostic images from a patient; a database comprising one or more
boundary parameters; a processor configured to compare the
retrieved images with the one or more boundary parameters; and an
alert system in communication with the imaging modality and
database configured to provide one or more alert for an urgent
medical condition if one or more of the images falls within the
boundary parameters.
[0020] In another aspect, a method for providing patient medical
diagnostic images comprises retrieving, using a processor, one or
more images associated with a patient from an image database or an
imaging device, the one or more images defining a set of images;
retrieving, historical data of said patient from a memory;
comparing, using a processor, the one or more images with the
historical data; and providing the one or more images and the
historical data to a reviewing physician
[0021] In another aspect, a system for providing medical diagnostic
images comprises an imaging modality for retrieving medical
diagnostic images from a patient; a database comprising historical
data of said patient; a processor configured to compare the
retrieved images with the historical data of said patient; and a
prioritizing, visualization and reporting system in communication
with the imaging modality and the database configured to provide
the images and the historical data to a reviewing physician.
[0022] In another aspect, a method for providing medical
diagnostics comprises providing access to one or more platforms
capable of distributing one or more applications for implementing a
method, the method comprising: retrieving, using a processor, one
or more images from an image database or an imaging device, the one
or more images defining a set of images; determining, using a
processor, whether each of the images is of medical interest to a
reviewing physician; and providing one or more images to a display
and analysis system for review by a reviewing physician, wherein
the one or more images are provided with an image that is
representative of the set of images.
[0023] In another aspect, a system for providing medical
diagnostics comprises one or more platforms capable of distributing
one or more applications for implementing a method, the method
comprising: retrieving, using a processor, one or more images from
an image database or an imaging device, the one or more images
defining a set of images; determining, using a processor, whether
each of the images is of medical interest to a reviewing physician;
and providing one or more images to a display and analysis system
for review by a reviewing physician, wherein the one or more images
are provided with an image that is representative of the set of
images. The system further comprises an interface configured to
receive one or more user input related to the distribution of the
one or more applications.
[0024] In another aspect, a method for providing medical diagnostic
images comprises (a) retrieving, with the aid of a processor, one
or more images from an image database or an imaging device, the one
or more images defining a set of images; (b) selecting, with the
aid of a processor, one or more images from the set of images based
on diagnostic data stored within a memory; (c) generating a report
including the one or more selected images and providing the report
to a reviewing physician; (d) receiving one or more modifications
to the report from the reviewing physician; and (e) updating the
diagnostic data based on the one or more modifications.
[0025] In another aspect, a method for providing medical diagnostic
images comprises (a) retrieving, with the aid of a processor, one
or more images from an image database or an imaging device, the one
or more images defining a set of images; (b) selecting one or more
images from the set of images based on diagnostic data stored
within a memory; (c) generating a report including the one or more
selected images; (d) providing the report to a reviewing physician;
(e) receiving subject outcome information relating to subject
responsiveness to treatment; and (f) updating the diagnostic data
based on the subject outcome information.
[0026] In another aspect, a system for providing medical diagnostic
images comprises (a) a database operatively coupled to an imaging
device, the database configured to store one or more images from
the imaging device, the one or more images defining a set of
images; and (b) a processor coupled to said database, wherein said
processor is programmed to: (i) generate a report from one or more
images selected from the set of images and provide the report for
review by a reviewing physician, wherein said one or more images
are selected based on diagnostic data stored in the database; (ii)
receive one or more modifications to the report from the reviewing
physician; and (iii) update the diagnostic data based on the one or
more modifications.
[0027] In another aspect, a method for providing medical diagnostic
images comprises (a) retrieving, with the aid of a processor, one
or more images from an image database or an imaging device, the one
or more images defining a set of images; (b) retrieving, one or
more boundary parameters from a memory location coupled to said
processor; (c) determining whether each of the images falls within
said boundary parameters; and (d) providing one or more alerts for
an urgent medical condition if, based on said determining of (c), a
given image among said one or more of images falls within the
boundary parameters.
[0028] In another aspect, a system for providing medical diagnostic
images comprises (a) an imaging modality for retrieving medical
diagnostic images from a subject; (b) a database comprising one or
more boundary parameters; (c) a processor coupled to said imaging
modality and said database, wherein said processor is programmed to
compare images retrieved from said imaging modality with the one or
more boundary parameters; and (d) an alert system in communication
with the imaging modality and said database, wherein said alert
system is configured to provide one or more alerts for an urgent
medical condition if one or more of said images fall within the
boundary parameters.
[0029] In another aspect, a method for providing subject medical
diagnostic images comprises (a) retrieving, with the aid of
processor, one or more images associated with a subject from an
image database or an imaging device, the one or more images
defining a set of images; (b) retrieving, historical data of said
subject from a memory location; (c) comparing, with the aid of a
processor, the one or more images with the historical data; and (d)
providing the one or more images and the historical data to a
reviewing physician.
[0030] In another aspect, a system for providing medical diagnostic
images comprises (a) an imaging modality for retrieving medical
diagnostic images from a subject; (b) a database comprising
historical data of said subject; (c) a processor programmed to
compare the retrieved images with the historical data of said
subject; and (d) a prioritizing, visualization and reporting system
in communication with the imaging modality and the database,
wherein said prioritizing, visualization and reporting system
provides the images and the historical data to a reviewing
physician.
[0031] In another aspect, a method for providing medical
diagnostics comprises (a) providing access to one or more platforms
programmed to distribute one or more applications which, upon
execution by a processor, implement a method, the method
comprising: (i) retrieving, with the aid of a processor, one or
more images from an image database or an imaging device, the one or
more images defining a set of images; (ii) determining, with the
aid of a processor, whether each of the images is of medical
interest to a reviewing physician; and (iii) providing one or more
images to a display and analysis system for review by a reviewing
physician, wherein the one or more images are provided with an
image that is representative of the set of images.
[0032] In another aspect, a system for providing medical
diagnostics comprises (a) one or more platforms programmed to
distribute one or more applications which, upon execution by a
processor, implement a method, the method comprising: (i)
retrieving, with the aid of a processor, one or more images from an
image database or an imaging device, the one or more images
defining a set of images; (ii) determining, with the aid of a
processor, whether each of the images is of medical interest to a
reviewing physician; and (iii) providing one or more images to a
display and analysis system for review by a reviewing physician,
wherein the one or more images are provided with an image that is
representative of the set of images. The system further comprises
(b) a user interface adapted to receive one or more user inputs
related to the distribution of the one or more applications.
[0033] Additional aspects and advantages of the present disclosure
will become readily apparent to those skilled in this art from the
following detailed description, wherein only illustrative
embodiments of the present disclosure are shown and described. As
will be realized, the present disclosure is capable of other and
different embodiments, and its several details are capable of
modifications in various obvious respects, all without departing
from the disclosure. Accordingly, the drawings and description are
to be regarded as illustrative in nature, and not as
restrictive.
INCORPORATION BY REFERENCE
[0034] All publications, patents, and patent applications mentioned
in this specification are herein incorporated by reference to the
same extent as if each individual publication, patent, or patent
application was specifically and individually indicated to be
incorporated by reference.
BRIEF DESCRIPTION OF THE DRAWINGS
[0035] The novel features of the invention are set forth with
particularity in the appended claims. A better understanding of the
features and advantages of the invention will be obtained by
reference to the following detailed description that sets forth
illustrative embodiments, in which the principles of the invention
are utilized, and the accompanying drawings (also "FIG." herein),
of which:
[0036] FIG. 1 shows a medical imaging workflow with a timeline, in
accordance with an exemplary embodiment of the current art;
[0037] FIG. 2 shows an examination workflow, in accordance with an
embodiment of the invention;
[0038] FIG. 3 shows a picture analysis prioritization visualization
and reporting ("PAPVR") system as part of a workflow system, in
accordance with an embodiment of the invention;
[0039] FIG. 4 shows a CT scan of a patient's pleural cavity, in
accordance with an embodiment of the invention;
[0040] FIG. 5 shows steps taken in flagging an image as a
representative image, in accordance with an embodiment of the
invention;
[0041] FIG. 6 shows a series of steps for prioritizing medical
images, in accordance with an embodiment of the invention;
[0042] FIG. 7 is a screenshot of a patient case queue and the
indication of priority of each case in the queue, in accordance
with an embodiment of the invention;
[0043] FIG. 8 is a screenshot of an interactive window, in
accordance with an embodiment of the invention;
[0044] FIG. 9 is an exemplary overview of a computer system as may
be used in any of the various locations throughout the system and
method disclosed herein;
[0045] FIG. 10 is an exemplary overview of a network-based system,
in accordance with an embodiment of the invention; and
[0046] FIG. 11 is an exemplary revised timeline for the medical
imaging workflow shown in FIG. 1, in accordance with an embodiment
of the invention;
[0047] FIG. 12 shows an exemplary process for tracking outcomes of
final reports and matching to differences in images;
[0048] FIG. 13 shows an exemplary process 1300 for follow-up of
post-visit patient history;
[0049] FIG. 14a shows an exemplary process for implementing an
enhanced alert system;
[0050] FIG. 14b shows an exemplary process for an optional
continuation of the process of FIG. 14a;
[0051] FIG. 15 shows an exemplary process for the implementation of
an enhanced analytics system;
[0052] FIG. 16 shows an exemplary process for the analysis of
patient medical data;
[0053] FIG. 17 shows two exemplary screens of systems and methods
disclosed herein;
[0054] FIG. 18 shows an exemplary process for user interaction with
app store modules;
[0055] FIG. 19 shows an overview of an exemplary app store
environment; and
[0056] FIG. 20 shows an exemplary process for app store
transactions.
DETAILED DESCRIPTION
[0057] While various embodiments of the invention have been shown
and described herein, it will be obvious to those skilled in the
art that such embodiments are provided by way of example only.
Numerous variations, changes, and substitutions will now occur to
those skilled in the art without departing from the invention. It
should be understood that various alternatives to the embodiments
of the invention described herein may be employed in practicing the
invention.
[0058] In view of the various limitations of current medical image
retrieval and processing systems, there is recognized herein a need
for improved imaging, analysis, prioritization and reporting
systems. In particular, there is recognized herein a need for
methods and systems for accurately and efficiently analyzing and
prioritizing medical images, such as images acquired from CT scans
and MRIs, to provide better patient (or subject) risk
management.
[0059] Some embodiments provide a system and method for using a
computer to retrieve images from a database and to determine
whether each of the images is of medical interest to a reviewing
physician. In some cases, system and method are provided for using
the computer to determine which one (or more) of the images is
representative of the full set of images and providing that
representative image or images to a display and analysis system for
review by a reviewing physician, so the patient outcome may be
tracked by continuously following the initial findings and the
responsiveness to treatment, and also by tracking the clinical
diagnosis and comparing that with initial radiological findings and
then following up in clinical treatment up to full resolution of
the problem to determine whether the initial findings were
supported or not, and if not, what the discrepancies are. By
tracking patient outcome the diagnostics can be further enhanced
and refined over time, thus improving the results.
[0060] Some embodiments provide a system and method for machine
learning at two levels, a first level and a second level. On the
first level, the system looks at the final report by a radiologist
and compares it to the system's automatically generated preliminary
report, adjusting/refining algorithms to more closely match the
radiologist's report. This approach involves automatic processing
of many cases and using analytics/statistical processing of vast
amounts of data to improve diagnostic algorithms and hence patients
outcome. The second level requires tracking the patient outcomes
beyond the radiological report, e.g., reports by referring
physician, other, to better understand patient's real condition and
automatically refining algorithms to better match real patient
condition.
[0061] Some embodiments provide a system and method to alert
physicians to potentially serious findings in as close as possible
to real time. Some embodiments provide a system and method for
supporting comparisons between current and historical data, both to
the individual and to peer groups.
[0062] In some cases, a user may need to download additional
modules for the system and method disclosed throughout herein. In
current practice, a user may download additional modules and
features for an existing system from an application ("app")
store.
[0063] Some embodiments provide a system and method in an app store
environment, including an application management module and the
actual store itself from which users may download, evaluate, and
purchase apps.
[0064] Some applications may be downloaded that are for research
use only, because these applications are not approved for medical
use by a regulatory body (e.g., the United States Food and Drug
Administration, "FDA") charged with regulating the use and/or
distribution of the applications. These applications may be
activated only when the system and method disclosed herein
throughout is in a "research only" mode. During said research mode,
no real patient data may be used for clinical or actual medical
purposes; the patient (or subject) data may be used solely for
research and testing purposes. When the system is in "clinical"
mode, all the unapproved applications must be suspended. In some
cases, the system may have various approval modes, such as a
different approval mode for each different regulatory agency.
[0065] For example, certain products and plug-ins may be approved
in Europe but not approved in the United States, or vice versa. In
a given system, multiple approval modes may be available, and a
user, such as a physician, may switch between modes. In a system
configured with multiple approval modes, one mode is designated the
default mode, usually determined by the system location (e.g.,
Europe or the U.S.) and purpose. If the system is not in its
default mode, an alert is displayed on screen, such as, for
example, a red blinking frame around the screen display as a
reminder that the system is in a non-default mode. For example, if
the system is being used in the U.S. in a mode other than the
default FDA-approved mode, a non-default mode indicator means some
of the modules in use are not FDA-approved. Any files and documents
created in a non-default mode may have a clear overlay imprint
showing, for example, "Not FDA approved," which may indicate that
the files and documents have not been approved for use by the
regulatory body (e.g., FDA) whose approval is required in the
default mode when the system is in use.
[0066] The invention provides methods and systems for analyzing and
prioritizing medical images, and for reporting medical findings.
For example, an analysis of medical images according to some
aspects of the system and methods disclosed herein may be used to
identify critical medical conditions, and, based on this analysis,
the system and method may further be used to organize a work list
for a reviewing physician based on the severity of the medical
findings and to then create a text document that lists the medical
findings in the analyzed medical images. For example, a database
may be created, showing a "normalized" version of each possible
aspect of a region. Accordingly, deviations above a certain
threshold may be used to flag a certain image. Furthermore, in some
areas, just the appearance of an unexpected presence (for example,
a liquid in the pleural space) maybe used to flag an image or a
series of images. It is clear that many variations can be done
without changing the spirit of the invention. Various aspects of
the invention described herein may be applied to any of the
particular applications set forth below or for any other types of
displays, or radiological data management applications. The
invention may be applied as a standalone system or method, or as
part of an integrated software package, such as a medical and/or
laboratory data management package or application, or as part of an
integrated picture archiving communication systems ("PACS")
solution. It shall be understood that different aspects of the
invention can be appreciated individually, collectively, or in
combination with each other.
[0067] Current medical imaging, processing and retrieval systems
are incapable of providing sufficient patient risk management. This
is due at least in part to the lack of case prioritization. In
addition, hospitals may not have the resources to review and
analyze each medical image in a set of medical images in a timely
manner, and current PACS do not provide physicians the resources to
efficiently and accurately analyze, prioritize, and report findings
in medical images.
[0068] In some embodiments of the invention, methods and systems
are provided for efficiently and accurately interpreting medical
images, acquiring quantitative measurements for each of the medical
images, and providing the reviewing physicians the capability to
generate medical reports. Methods and systems of embodiments of the
invention can provide hospitals with the capability to streamline
their medical image processing, which advantageously reduces the
time and resources necessary to review each scan (e.g., CT/CAT,
MRI, PET/CT) associated with a subject (e.g., patient), and provide
physicians accurate data necessary to provide adequate medical
care.
[0069] In some embodiments of the invention, methods and systems
are provided for analyzing medical images (e.g., CT scans of the
chest, abdomen, and head). Methods and systems of embodiments of
the invention improve the quality of patient care by automatically
prioritizing cases prior to review by a reviewing physician or
specialist (e.g., radiologist) based on pathological findings. In
various embodiments, methods and systems for analyzing and
prioritizing medical images generate preliminary reports, which are
available to reviewing physicians as they open cases for review.
This advantageously reduces the time it takes a radiologist to
prepare a final report. The report can include additional
information, such as quantified measurements (e.g., cross-sectional
areas, volumes) automatically extracted, generated, or calculated
from the data. Methods and systems of embodiments of the invention
can seamlessly integrate into an existing radiological
workflow.
[0070] With reference to FIG. 1, a typical medical imaging workflow
as currently used is shown. Approximate lengths of time associated
with each step in the workflow are also indicated in the figure.
Such times are provided by way of example only. It will be
appreciated that other times are possible.
[0071] Initially, in step 101, a patient is admitted to a hospital
or other healthcare provider for treatment or a routine checkup.
For example, the patient may be admitted through the emergency room
("ER"), the in-patient unit, or the out-patient unit of a
healthcare provider. An admitting physician or nurse conducts a
preliminary examination of the patient to determine whether the
patient's condition warrants immediate medical attention (i.e.,
"Stat" or "No-Stat"). For instance, the admitting physician can
determine whether the patient's condition is of high or low
priority. The admitting physician or nurse may indicate the
patient's status (e.g., high priority, low priority) in a patient
tracking system, such as the patient tracking feature of a
radiology information system ("RIS"). The admitting physician or
nurse can also indicate "Stat" or "Non-Stat" (or "No-Stat"). Cases
indicated as "Stat" may be placed in a high priority queue while
cases indicated as "No-Stat" can be placed in a low priority
queue.
[0072] With continued reference to FIG. 1, in a patient examination
step 102, medical images (e.g., CAT/CT scan, MRI, PET/CT scan) are
obtained from a patient. Medical images may be obtained using a
variety of methods. For example, a three-dimensional image (with
2-D cross-sections) of a particular region of a patient's body may
be obtained using a CT scanner. As another example, a
three-dimensional image may be obtained using an MRI. Such
three-dimensional image may have two-dimensional cross-sectional
images. Alternatively, multiple images may be provided, whether
they originate from a three-dimensional image or not. Medical
images (or scans) thus obtained are stored in a PACS. The PACS
makes these images available for review by a reviewing physician or
specialist (e.g., radiologist).
[0073] Next, in step 103, a radiologist retrieves and interprets
the images obtained during the patient examination step. The
radiologist reviews all of the images in a case in step 104.
[0074] In the next step 105, the radiologist prepares a report
having the radiologist's analysis of the patient's medical images.
The radiologist might dictate (or type) a report comprising the
radiologist's diagnosis of the patient's condition. The radiologist
may add to the report images taken from the case that show visual
representation of the diagnosis ("Key Images"). The radiologist can
then make the report available for review by a referring
physician.
Picture Analysis Prioritization Visualization and Reporting
System
[0075] In an aspect of the invention, a computer system is provided
for improving the efficiency and accuracy of a workflow process. In
some embodiments of the invention, the computer system, which, for
example, could be a standard personal computer with a standard CPU,
memory and storage, is an enhanced picture archiving communication
system, or an add-on subsystem to an existing PACS and/or RIS. In
some embodiments of the invention, the computer system can be
configured to analyze and prioritize images and patient cases. The
computer system can be referred to as a picture analysis
prioritization visualization and reporting system (also "PAPVR
system" herein). The computer system can automatically retrieve
medical images from an imaging modality (e.g., CAT/CT scanner, MRI,
PET/CT scanner) or a database in which medical images are stored,
or a PACS, automatically analyze the medical images, and provide
the medical images and the results of the analysis for review by a
reviewing or referring physician, or a specialist, such as a
radiologist.
[0076] With reference to FIG. 2, an examination workflow is
illustrated, in accordance with an embodiment of the invention. In
a first step 210, a patient is admitted for treatment or a routine
checkup. An admitting physician or nurse can determine whether the
patient's condition is of high priority or low priority. Next, in
step 215 a predetermined region of the patient's body is scanned.
In an embodiment, a predetermined region of the patient's body is
imaged using CT (or CAT) scan. In another embodiment, a
predetermined region of the patient's body can be imaged using MRI,
PET scan, or PET/CT scan. Scanning the patient can provide one or
more images (e.g., 2-D or 3-D images) of a predetermined region of
the patient's body. Next, in step 220 the one or more images (or
set of images) are stored in an image database. In an embodiment,
the image database can be a subsystem of a PACS. In another
embodiment, the image database can be a standalone computer system.
In such a case, the standalone computer system can be in
communication with a PACS.
[0077] With continued reference to FIG. 2, in step 225, the one or
more images are analyzed by a PAPVR system (or enhanced PACS), in
accordance with an embodiment of the invention. In an embodiment, a
subset of the one or more images is analyzed and interpreted by the
PAPVR system. Next, in step 230, the PAPVR system reviews the one
or more images to determine whether the one or more images would be
of interest (e.g., Key Images) to a reviewing or referring
physician. This can entail determining whether the one or more
images show any abnormalities with respect to the patient's
condition, for example, free pleural air (pneumothorax) or fluid,
aortic dissection, intracranial hemorrhage, liver metastases etc.
These various conditions, for example, can be determined using
comparable images, as well as comparing them to normalized images
as described throughout herein. In an embodiment, the PAPVR system
can determine whether each or a subset of the one or more images is
important for further review by a reviewing or referring physician.
In some cases, further the system may perform additional analysis,
including but not limited to providing quantitative measurements,
as well as, in some cases, the indication of the localization (for
example with an added color overlay that can be turned off for
better viewing, or other suitable methods) where the measurement
has been performed. This localization is more specific than a
keyframe as it may be a small region inside a key frame. For
example, When we detect blood in the pleural effusion (hemothorax),
we can highlight the areas where blood was detected into the
pleural effusion. This can save time in some cases since if blood
is detected correctly somewhere in the pleural effusion and the
radiologist is brought automatically to that place for
verification, the radiologist can diagnose the hemothorax without
further measuring liquid intensity in other slices.
[0078] Next, in step 235, the PAPVR system can perform quantitative
measurements and calculations (e.g., distances, cross-sectional
areas, volumes), that is relevant to the patient's condition, for
example, measuring the volume of air in a pneumothorax by doing
image analysis as described herein. Next, in step 240, the PAPVR
system can create a draft report that includes the findings,
calculations and Key Images. Next, in step 245, the PAPVR system
can designate case priority. Next, in step 250, the PAPVR system
can provide the one or more images and the draft report for review
and preparation of the final report by a reviewing or referring
physician. In an embodiment, the one or more images can be provided
with the PAPVR system's interpretation of the one or more images.
The steps 225, 230, 235, 240 and 245 can be collectively referred
to as step 255.
[0079] Further, in some cases, the system could be automatically
comparing the present study with a previous similar study obtained
on the same patient in the past; in these cases the invention can
compare findings and quantify changes such as increased pleural
fluid or increased dilatation of an aortic aneurysm which has
significant clinical implications.
[0080] In an aspect of the invention, methods for retrieving and
processing medical diagnostic images are provided. The methods
comprise using a computer system, such as an enhanced picture
archiving communication system (also "picture archiving
communication and analysis system" herein), to retrieve one or more
images (e.g., two-dimensional images from a three-dimensional scan)
from an image database or directly from an imaging device (e.g.,
imaging modality). In an embodiment, the one or more images define
a set of images. Next, the computer system determines whether each
of the images is of medical interest to a reviewing physician, for
example, by identifying the image that shows the point in which the
aorta is seen at its widest diameter, or, for example, by analyzing
that specific aspect in a series of volumetric images and
calculating the value, and then flagging the one with the largest
numeric value, either by dimension, area or any other suitable
measure. In an embodiment, this can include the computer system
comparing each of the images to images from patients with known
medical conditions. Next, the computer system determines whether
one or more of the images is representative of the set of images
and designates them as Key Images. The computer system then
provides the one or more images to a display and analysis system
for review by a reviewing physician. In addition, using the above
image comparisons, the computer system can detect whether a patient
suffers from a particular ailment, and provide a reviewing
physician quantitative information (e.g., distances,
cross-sectional areas, volumes), that is relevant to the patient's
condition.
[0081] In an aspect of the invention, a PAPVR system is provided
for automatically retrieving, reviewing and analyzing one or more
medical images acquired from an imaging modality. In some
embodiments, the PAPVR system can analyze and interpret each or a
subset of one or more images acquired by an examination system,
such as an imaging modality (e.g., CAT/CT scan, MRI, PET/CT scan).
In some case, the PAPVR system can be referred to as an enhanced or
improved PACS. The PAPVR system of preferable embodiments can
automatically perform step 255 of FIG. 2.
[0082] In preferable embodiments of the invention, the PAPVR system
is configured to automatically detect and quantify various
physiological features or abnormalities, for example, by using
image processing algorithms that identify the pneumothorax
condition, and other image processing algorithms that can segment
the area of the pneumothorax and calculate its volume, as discussed
exemplarily throughout this document. By automatically detecting
various physiological features or abnormalities, the PAPVR system
of embodiments of the invention can advantageously reduce the time
and resources required to review images provided from an imaging
modality (e.g., CT scan, MRI, PET/CT). This increases the accuracy
of detection and quantification, and provides for improved patient
care and more efficient workflow. PAPVR systems of embodiments of
the invention advantageously enable healthcare providers to provide
patients with accurate and rapid patient care.
[0083] With reference to FIG. 3, in an embodiment of the invention,
a PAPVR system 310 configured to retrieve, analyze and interpret
one or more images provided by an examination system is
illustrated, in accordance with an embodiment of the invention. The
PAPVR system 310 can include tangible, non-transitory computer
readable media. The PAPVR system 310 can be part of a healthcare
provider's workflow. In an embodiment, the PAPVR system can
automatically perform step 255 of FIG. 2. The PAPVR system 310 can
retrieve images from a storage unit that can be part of the PAPVR
system 310, or from a separate PACS system 325, and prepare the
images for review. The PAPVR system 310 can be in communication
with other components or computer systems (also "systems" herein)
of a healthcare provider. In an embodiment, the PAPVR system 310
can be physically situated at the location of a healthcare provider
(i.e., the PAPVR system can be on-site). In such a case, the PAPVR
system can communicate with other components or systems of the
healthcare provider via the healthcare provider's network, such as
an intranet. In another embodiment, the PAPVR system 310 can be an
off-site system that communicates with other components of a
healthcare provider via the Internet or World Wide Web.
[0084] With continued reference to FIG. 3, the PAPVR system 310 is
configured to retrieve one or more images from an examination
system 315 or a PACS 325; analyze and interpret (also referred to
as "process" herein) some or all of the one or more images; and
provide the one or more images for review by a referring or
treating physician. In an embodiment, following processing, the
PAPVR system 310 can provide the images to a reviewing system 320
configured to display the images to a physician. In an embodiment,
the PAPVR system 310 can analyze and interprets each cross-section
of a three-dimensional scan of a particular region of a patient's
body. The PAPVR system can contain, receive, or utilize computer
readable media, which may contain instructions, logic, data, or
code that may be stored in persistent or temporary memory of a
computer, or may somehow affect or initiate action by the PAPVR
systems, or any computers or servers contained therein. Any steps
or analysis described herein may be performed by utilizing such
computer readable media.
[0085] In some embodiments, the PAPVR system 310 can automatically
detect various physiological features, again, for example, by using
image processing algorithms that identify the pneumothorax
condition, and another image processing algorithm that can segment
the area of the pneumothorax and calculate its volume. For example,
the PAPVR system can automatically detect air and/or liquid pockets
and quantify (or calculate) the volume of the air and/or liquid
pockets. The PAPVR system can also quantify cross-sectional areas
and distances. In some embodiments, the PAPVR system can detect
bones and organs, and quantify the cross-sectional areas and/or
volumes of the bones and organs.
[0086] In some embodiments, the PAPVR system 310 can provide
additional data with each of the one or more images. The PAPVR
system 310 can provide the additional data for review by a
reviewing or referring physician (using the reviewing system 320,
for example). The additional data can include distances (e.g.,
distances between features) cross-sectional areas, gas (e.g., air)
volumes, liquid (e.g., blood) volumes, blood vessel cross-sectional
measurements, location and number of bone fractures, and shift in
the position of body organs such as the mediastinum in tension
pneumothorax. In an embodiment, when a physician accesses each of
the one or more images, the additional data is made accessible to
the physician. In an embodiment, when the physician views a
two-dimensional cross-sectional image of a three-dimensional image,
the additional data is provided with each two-dimensional
cross-sectional image. In some embodiments, additional data may be
provided with each image by way of metadata associated with each
image.
[0087] With continued reference to FIG. 3, the PAPVR system 310 can
be in communication with other systems or components associated
with the healthcare provider's workflow system. In some
embodiments, the PAPVR system 310 can be in communication with one
or more of an imaging modality (e.g., CAT/CT scan, MRI, PET/CT
scan) remote backup system, a DICOM storage and PACS server 325, a
PACStoGO system, a CD/DVD publishing system and a film digitizer.
The PAPVR system 310 can be in communication with other workflow
systems and/or components via an intranet, the Internet (e.g.,
wired or wireless web), or other mode of communication, such as
Bluetooth. In some embodiments, the PAPVR system can be configured
to interact manually or automatically with one or more systems or
components associated with a workflow system.
[0088] FIG. 4 shows one image of a CT scan 400 processed by a PAPVR
system of embodiments of the invention. The image 400 is a
two-dimensional cross-sectional image of a patient's pleural
cavity. The image 400 is one example of an image among many images
that can be provided from a CT scan. The CT scan shows free pleural
effusion, free pleural air and mediastinal shift (=tension
hydropneumothorax) 405 and the patient's rib cage 410. In some
embodiments, the PAPVR system is configured to automatically detect
a pleural effusion and quantify the volume of free liquid and free
air in the patient's pleural cavity and identify the mediastinal
shift which suggest a medical emergency. In an embodiment, the
PAPVR system can also automatically detect the presence of an air
volume or space (e.g., pneumo-thorax) and quantify the volume. In
some embodiments, the PAPVR system can automatically detect and
quantify various physiological features or abnormalities, such as,
e.g., pneumothorax, tension pneumothorax, pleural effusion,
ascending and descending aortic caliber and aortic dissections.
Key Image
[0089] In an aspect of the invention, a PAPVR system can be
configured to provide a radiologist or other reviewing physician
with one or more images, Key Images, that are representative of a
set of images and/or representative of the patient's condition.
[0090] With reference to FIG. 5, in an embodiment, a PAPVR system
can automatically identify one or more images as Key Images, based
on, for example, the image that shows the aorta at its widest. In
an embodiment, a Key Image is an image that is representative of a
set of images. In another embodiment, a Key Image is representative
of the patient's condition. In such a case, the Key Image can best
capture the patient's condition. In some cases, the Key Image can
accurately define a set of images. For instance, if a patient's CT
scan shows a pleural effusion, the Key Image can be the image
(e.g., two-dimensional cross-sectional image) determined by the
PAPVR system to clearly and accurately show the pleural effusion.
In some embodiments, when the PAPVR system provides one or more
images and data for review by a reviewing (such as a radiologist)
or referring physician, the Key Image can be the first image the
reviewing physician observes. In other embodiments, the Key Images
provided by the PAPVR system can be the images used by the
reviewing physician in the final report prepared for the referring
physician. For example, a Key Image can be found by comparing
tissue density of certain sections with average examples (i.e.,
liquids have a different density than "normal tissue") or
structural abnormalities, such as "speckles" of another density,
which could indicate for example tumors, or fracture lines in a
bone, etc.
[0091] With continued reference to FIG. 5, in a first step 505, the
PAPVR system retrieves an image (e.g., two-dimensional
cross-section of a three-dimensional image or scan) for processing.
Next, in step 510, the PAPVR system determines whether a reviewing
physician would consider the image representative of the set of
images. If the image is determined to be representative of the set
of images, in step 515 the image is flagged as a "Key Image." If
the image is determined to not be representative of the set of
images, in step 520 the image is not flagged as a "Key Image."
Next, in step 525, the set of images or a subset of the set of
images is provided to a reviewing (or treating) physician for
review. In an alternative embodiment, if an image is not found to
be representative, the PAPVR system can skip step 515 and proceed
directly to step 525.
Image Prioritization
[0092] In an aspect of the invention, a PAPVR system can
automatically prioritize an image. Image prioritization can
advantageously reduce time and resources required by a reviewing or
treating physician to make an accurate diagnosis. In some
embodiments, the PAPVR system can flag some images as having a
higher priority relative to other images, and a physician or
radiologist can review only those images, thus saving considerable
time in analyzing images associated with a particular scan.
[0093] A PAPVR system of embodiments of the invention can
automatically prioritize an image. In an embodiment, the PAPVR
system can be configured to flag an image as having a "high
priority" or a "low priority." In other embodiments, the PAPVR
system can flag an image as having high, medium or low priority. In
an embodiment, the PAPVR system can categorize an image among a
predetermined number of categories. For example, one, two, three,
four, five, six, seven, eight, or more categories may be utilized.
In still other embodiments, the PAPVR system can assign a numerical
value (e.g., 1-10, 1-100, 1-1000, 1-10,000) to an image that is
indicative of the priority of the image. For example, a high
priority image can be assigned a numerical value of 1, while a low
priority image can be assigned a numerical value of 100. In some
embodiments, the user can specify how an image is to be
prioritized. For example, the user can specify that images are to
be prioritized as high, medium, or low priority.
[0094] In some embodiments, a user (e.g., a reviewing/referring
physician, radiologist) can request that the PAPVR system only
provide images having a priority that is above a minimum (or
cut-off) priority. For example, the user can request that the
system provide only high priority images for review. As another
example, the user can request that the PAPVR system provide images
having a priority numerical value above a certain value or within a
certain range. In some embodiments, the user can specify the
minimum (cut-off) priority.
[0095] With reference to FIG. 6, in an embodiment of the invention,
a method for prioritizing an image from an imaging modality is
provided. In a first step 605, the PAPVR system retrieves images
for review. Next, in step 610, the PAPVR system determines whether
a reviewing or treating physician, such as a radiologist, would
consider each image important. In an embodiment, step 610 can
entail comparing each image to images from patients with known
conditions to determine whether there is a match. In an embodiment,
the PAPVR system can access an image database for image comparison.
If the image under review is found by the PAPVR system to be
important, in step 615 that image can be flagged as a "high
priority" image. If the image is not found to be important (or if
it is found to be unimportant), in step 620 that image can be
flagged as "low priority." Next, in step 625, the PAPVR system
prepares the images for review by a reviewing or treating
physician.
[0096] In an embodiment, the PAPVR system can assign a priority
value to an image based on the degree that the image matches one or
more images from one or more patients with a known condition. Such
matching can be accomplished by comparing the image under review by
the PAPVR system to images from an image database. A higher
priority value can be assigned to images that match known
conditions (or physiological abnormalities) while a low priority
can be assigned to images that do not match any known condition.
For example, if an image under review matches an image from a
patient with tension pneumo-thorax, that image can be assigned a
high priority value. In some cases, a reverse priority value can be
assigned, in which case a priority value is assigned based on the
degree to which a given image matches one or more images from
patients with no known conditions.
Case Prioritization
[0097] In another aspect of the invention, the PAPVR system can
automatically prioritize patient cases. In various embodiments, the
PAPVR system can automatically identify various medical conditions
and assign that case a certain priority. The priorities assigned to
the cases can be relative priorities (i.e., the PAPVR system
determines that one case is of higher priority relative to another
case in the queue of cases for a reviewing physician).
Alternatively, the PAPVR system can prioritize cases based on
absolute priority, which can entail prioritizing cases with
patients having life-threatening conditions as high priority cases
and patients without life-threatening conditions as low priority
cases. The rules used by the PAPVR system to determine case
priorities are configurable by the reviewing physician and the
medical institution.
[0098] In an embodiment, the PAPVR system can automatically review
a patient's images to determine whether the patient requires
immediate medical care. If the PAPVR system determines that the
patient requires immediate medical care, the PAPVR system can flag
the patient's case as high priority. Otherwise, the PAPVR system
can flag the patient's case as a lower priority (e.g., medium
priority, low priority) case.
[0099] With reference to FIG. 7, a screenshot of a patient case
queue for a reviewing physician 700 is shown. The case queue
includes a column 705 having a date and time stamp for each case, a
column 710 with the modality (e.g., CAT/CT scan, MRI, PET/CT scan)
used to acquire images, a column 715 showing the body part
associated with each case, and a column 720 showing the priority
associated with each case. The priority for each case can be
indicated by a colored circle, with the color red indicating high
priority, the color orange indicating medium priority, and the
color green indicating low priority. Alternatively, the priority
for each case can be indicated by a numerical value (e.g., 1-10,
1-100, 1-1000).
[0100] In an embodiment of the invention, the PAPVR system can
automatically update case priorities. This can advantageously
enable a reviewing physician, such as a radiologist, to be aware of
the highest priority cases, such that these cases are reviewed
first by the reviewing physician, and thus enable the referring or
treating physician to get the reviewing physician's report sooner
than if all cases were assigned the same priority. This capability
of the PAPVR system can significantly shorten the time interval
between when a patient is tested (e.g., with a CAT/CT scan, MRI,
PET/CT scan) and when a patient is treated by the referring or
treating physician after receiving the report from the reviewing
physician. For example, if a case queue (such as queue 700 of FIG.
7) includes 10 cases with 1 case having high priority, 5 cases
having medium priority and 4 cases having low priority, after the
high priority case has been reviewed, the PAPVR system can
reclassify the 9 remaining cases. This might entail reprioritizing
the cases. In such fashion, the priorities assigned to the cases
might be relative priorities (i.e., one case is of higher priority
relative to another case). Alternatively, the PAPVR system can
prioritize cases based on absolute priority, which might entail
prioritizing cases with patients having life-threatening conditions
as high priority cases.
[0101] In some embodiments, the PAPVR can optionally sort cases by
priority. In an embodiment, the PAPVR system can sort cases in
descending order based on priority. For example, the PAPVR system
can display high-priority cases at the top of the queue and low
priority cases at the bottom of the queue.
Case Review and Reporting
[0102] In an aspect of the invention, the PAPVR system can provide
one or more images associated with a particular patient, in
addition to data associated with each image, to a radiologist (or
other reviewing physician) for review. In a preferable embodiment,
the PAPVR system provides a radiologist an assessment of each
image. In an embodiment, the PAPVR system can determine whether a
particular ailment or abnormality is present in an image, and
provide its assessment (e.g., "A pleural effusion has been
detected") to a reviewing physician. The PAPVR system of preferable
embodiments of the invention can enable improved patient outcomes
and increased productivity.
[0103] FIG. 8 an interactive window 800 that enables a radiologist
to review images associated with each case, in addition to data
provided by the PAPVR system. The interactive window 800 can also
permit a radiologist to provide notes, including her/his assessment
of the patient's condition. With continued reference to FIG. 8, the
interactive window 800 includes a case or scan selection panel (or
list) 805, a window 810 for displaying an image selected from the
panel 805, an interactive report window 815 with information
relevant to each image in the image window 810, a findings
navigator window 820 that indicates the ailments or conditions
(e.g., right pleural effusion) identified by the PAPVR system for
the reviewed scan, and menu features 825 to permit a radiologist
(or other reviewing physician) to generate a report and change the
image visualization parameters (e.g., contrast or brightness),
resize and center the window 810. The interactive report window 815
can include the patient's identification ("ID") number, the
modality (CAT/CT scan, MRI, PET/CT scan) used to acquire the
images, and the PAPVR system's assessment of the patient's
condition. The interactive report window 815 can include other
information, such as whether the priority associated with the
patient's case, whether the image displayed in the window 810 is a
Key Image, and whether the image displayed in the window 810 is a
high priority image. The interactive report window 815 also permits
a radiologist to provide additional information, such as additional
findings with respect to the image shown in the window 810, and to
edit the information provided by the PAPVR system.
[0104] In various embodiments, the findings navigator window 820
can be used by the reviewing physician to quickly navigate to and
visualize in the image display window 810 Key Images the PAPVR
system automatically associated with each of the findings that are
listed in the findings navigator window 820. The PAPVR system can
automatically adjust the visualization parameters of the image
(e.g., contrast, brightness), or part of the image (e.g.,
highlighting the body organ in which an ailment was detected by the
PAPVR system) displayed in the image display window 810 to help the
reviewing physician better see or visualize the particular finding
or findings.
[0105] In an embodiment, a PAPVR system prioritizes cases and
provides the cases for review by a reviewing physician, such as a
radiologist. The radiologist can use a computer terminal in
communication with the PAPVR system to select the case of highest
priority from the case queue (such as case queue 700 of FIG. 7). In
an embodiment, the radiologist can use a reviewing system, such as
the reviewing system 320 of FIG. 3, to retrieve a case. Next, the
PAPVR system provides the radiologist an interactive window (such
as interactive window 800 of FIG. 8) with images (e.g.,
two-dimensional cross-sections) from a particular region of a
patient's body. In the interactive window the PAPVR system can
provide its assessment of the patient's condition. The PAPVR system
can permit the radiologist to provide additional information to the
patient's case. The PAPVR system can also provide a radiologist
additional information relevant to a particular image, such as
distances, cross-sectional areas, and volumes.
Systems
[0106] The disclosure provides computer systems for implementing
the methods provided herein. A computer system can be a computer
server ("server") that can be configured (e.g., programmed) to
retrieve, process and analyze medical images. The server, in some
examples, can include a data communication interface for packet
data communication. The server can also include a central
processing unit (CPU), in the form of one or more computer
processors (also "processors" herein), for executing program
instructions. The server platform can include an internal
communication bus, program storage and data storage for various
data files to be processed and/or communicated by the server,
although the server can receive programming and data via network
communications. The hardware elements, operating systems and
programming languages of such servers are conventional in nature,
and it is presumed that those skilled in the art are adequately
familiar therewith. Of course, the server functions can be
implemented in a distributed fashion on a number of similar
platforms, to distribute the processing load.
[0107] Aspects of the methods outlined herein can be embodied in
programming. Program aspects of the technology can be thought of as
"products" or "articles of manufacture" typically in the form of
executable code and/or associated data that is carried on or
embodied in a type of machine-readable medium. "Storage" type media
can include any or all of the tangible memory of the computers,
processors or the like, or associated modules thereof, such as
various semiconductor memories, tape drives, disk drives and the
like, which can provide non-transitory storage at any time for the
software programming. All or portions of the software can at times
be communicated through the Internet or various other
telecommunication networks. Such communications, for example, can
enable loading of the software from one computer or computer
processor (also "processor" herein) into another, for example, from
a management server or host computer into the computer platform of
an application server. Thus, another type of media that can bear
the software elements includes optical, electrical and
electromagnetic waves, such as used across physical interfaces
between local devices, through wired and optical landline networks
and over various air-links. The physical elements that carry such
waves, such as wired or wireless links, optical links or the like,
also can be considered as media bearing the software. As used
herein, unless restricted to non-transitory, tangible "storage"
media, terms such as computer or machine "readable medium" refer to
any medium that participates in providing instructions to a
processor for execution.
[0108] Hence, a machine-readable medium can take many forms,
including but not limited to, a tangible storage medium, a carrier
wave medium or physical transmission medium. Nonvolatile storage
media include, for example, optical or magnetic disks, such as any
of the storage devices in any computer(s) or the like, such as can
be used to implement the databases, etc. shown in the drawings.
Volatile storage media include dynamic memory, such as main memory
of such a computer platform. Tangible transmission media include
coaxial cables; copper wire and fiber optics, including the wires
that comprise a bus within a computer system. Carrier-wave
transmission media can take the form of electric or electromagnetic
signals, or acoustic or light waves such as those generated during
radio frequency (RF) and infrared (IR) data communications. Common
forms of computer-readable media therefore include for example: a
floppy disk, a flexible disk, hard disk, magnetic tape, any other
magnetic medium, a CD-ROM, DVD or DVD-ROM, any other optical
medium, punch cards paper tape, any other physical storage medium
with patterns of holes, a RAM, a ROM, a PROM and EPROM, a
FLASH-EPROM, any other memory chip or cartridge, a carrier wave
transporting data or instructions, cables or links transporting
such a carrier wave, or any other medium from which a computer can
read programming code and/or data. Many of these forms of computer
readable media can be involved in carrying one or more sequences of
one or more instructions to a processor for execution.
[0109] Various features of systems and methods of the disclosure
may be implemented with the aid of applications (or "apps")
operated on electronic devices, such as portable electronic
devices. Portable electronic devices can include portable computers
(e.g., Apple.RTM. MacBook Pro), tablet personal computers (e.g.,
Apple.RTM. iPad, Samsung.RTM. Galaxy Tab), and Smart phones (e.g.,
Apple.RTM. iPhone, Android-enabled phones).
[0110] FIG. 9 schematically illustrates computer system 900 that
can be used with systems and methods of the disclosure. The
computer system 900 can be used to execute code to process data.
Various modifications and changes may be made to computer system
900 without departing from the broader spirit and scope of the
system and method disclosed herein. A central processing unit (CPU)
901 is connected to a bus 902, which bus is connected to a memory
903, nonvolatile memory 904, display 907, I/O unit 908, and network
interface card (NIC) 913. I/O unit 908 may, typically, be connected
to keyboard 909, pointing device 910, hard disk (or in some cases
other suitable storage, including, but not limited to solid state
disk, RAID, network attached storage, storage area network, etc.
912, and real-time clock 911. NIC 913 connects to network 914,
which may be the Internet or a local network, which local network
may or may not have connections to the Internet. Also shown as part
of system 900 is power supply unit 905 connected, in this example,
to ac supply 906. Not shown are batteries that could be present,
and many other devices, including but not limited to special
enhanced pointing or navigational devices, such as mice, jog
wheels, etc, microphone(s) and speaker(s) and/or headset(s) for
recording and or playing back audio, and other modifications that
are well known but are not applicable to the specific novel
functions of the current system and method disclosed herein.
[0111] FIG. 10 shows a simplified overview of an exemplary PAPVR
system 1000 in an Internet- or other network-based implementation,
according to one aspect of the system and method disclosed herein.
In an embodiment of the invention, the PAPVR system can be seen as
a software 1005x running on server 1004 connected to a network 1002
(the Internet or a private network, or combination), having a local
repository 1006, as well as additional software instances 1005a-n
including such as operating system, networking software, image
processing software and any other suitable or needed software. The
system presents all images acquired from an imaging modality (e.g.,
CAT/CT scan 1021a, MRI 1021b, PET/CT scan 1021c, etc.) in one
exemplary location in a hospital 1020 to a reviewing physician at a
terminal or computing device 1021r in said hospital. In this
example, the PAPVR is off site, and the physician views images in
the hospital, but processing may happen off site. Additionally,
patient data may be encrypted, so patient confidentiality is
protected, etc. In an embodiment, the PAPVR system can first
present the reviewing physician with the one or more Key Images
(and data associated with the one or more representative images)
and provide the reviewing physician the option to review the other
(i.e., non-representative) images. In an embodiment, the
non-representative images (and data associated with the
non-representative images) can be viewed after the reviewing
physician has viewed the one or more Key Images. By prioritizing
transmission of key images, valuable minutes in an emergency room
can be saved, for example. Also shown is a local storage 1021d.
[0112] Exemplary hospital 1001 may be in a remote location and use
wireless communication to provide the same services to its
physicians and patients, etc., having the same or similar equipment
1001 a-n, analogous to 1021a-n.
[0113] FIG. 11 shows an enhanced work flow with work times amended
from those in FIG. 1, showing the time savings for steps for
enhanced steps 1102, 1103, 1104 and 1105, which are analogous to,
but improved as described herein, steps 102, 103, 104 and 105 of
FIG. 1, with respectively revised times 1112, 1113, 114, and 1115.
The PAPVR system 1120 generates items 1121a-n for the physician and
other medical personnel.
[0114] In some other embodiments, the PAPVR system may present the
reviewing physician the images in order of priority. In some
embodiments, only the higher priority images may be displayed to
the reviewing physician. Alternatively, all of the images, starting
with the higher priority images may be displayed to the
physician.
[0115] In some embodiments, the system may use a Key Image, or a
high priority image, to assist a physician with generating a
report. In some embodiments, the default images for a report may be
Key Images. A physician may be presented with the option of
changing the image for the report. Alternatively, the physician may
make an initial selection of the image(s) to be included within the
report. This may help streamline the medical review process, and
the report generation process.
[0116] While various embodiments of the invention have made
reference to a "scan" or "scans," it will be appreciated that any
use or reference to a "scan" or "scans" can refer to any type of
image. In an example, a "scan" refers to a medical image or a
diagnostic image. In another example, "scans" refer to multiple
medical images.
[0117] It will be appreciated that PAPVR systems and methods
described in various embodiments of the invention can be integrated
in (or used with) other systems and/or methods, such as, for
example, medical or diagnostic systems and/or methods, both in part
or in whole.
Enhanced Patient Outcome Tracking
[0118] In another aspect of the invention, systems and methods for
patient outcome tracking are provided. In some embodiments,
processes for tracking outcomes of final reports are described.
[0119] In some embodiments, methods for providing medical
diagnostic images comprise retrieving, using a processor, one or
more images from an image database or an imaging device, the one or
more images defining a set of images. Next, one or more images from
the set of images are selected based on diagnostic data stored
within a memory. Next, a report is generated including the one or
more selected images, and the report is provided to a reviewing
physician. One or more modifications to the report are received
from the reviewing physician. The diagnostic data is then updated
based on the one or more modifications. The memory may be formed of
one or more databases. In some situations, one or more additional
images defining an additional set of images are retrieved using a
processor, and one or more images are selected from the additional
set of images based on the updated diagnostic data.
[0120] In some cases, the diagnostic data is stored in a diagnostic
table, and updating diagnostic data includes updating the
diagnostic table. The diagnostic table is stored in a memory
location.
[0121] In some embodiments, methods for providing medical
diagnostic images comprise retrieving, using a processor, one or
more images from an image database or an imaging device, the one or
more images defining a set of images. Next, one or more images from
the set of images are selected based on diagnostic data stored
within a memory. Next, a report is generated including the one or
more selected images, and the report is provided to a reviewing
physician. Patient outcome information relating to patient
responsiveness to treatment is received, and the diagnostic data
based on the patient outcome information is updated. In some cases,
the methods comprise receiving a clinical diagnosis for a patient
associated with the set of images, receiving initial radiological
findings for the patient, retrieving one or more images multiple
times during treatment of the patient, and determining whether the
initial radiological findings were supported.
[0122] In some situations, the diagnostic data is updated with
information related to the discrepancy (also "discrepancy-related
information" herein) if the initial radiological findings were not
supported. One or more modifications to the report may be received
from the reviewing physician, and the diagnostic data may be
subsequently updated based on the modification.
[0123] FIG. 12 shows an exemplary process 1200 for tracking
outcomes of final reports and matching to differences in images, in
accordance with an embodiment of the invention. In step 1201, a
list of images, with the images accessible or attached thereto, is
received from a repository 1021d. Any networked or otherwise
connected (or operatively coupled) repository may be used in
addition to, or in lieu of, repository 1021d. In step 1202, this
list is analyzed with the images available for this case. Next, in
step 1203, the system selects "outlier" images that have strong
characteristics that deviate from a normal image and therefore are
most likely to be representative of the specific condition. The
selection in step 1203 can be made with the aid of a processor. In
step 1204 those images are presented for review by a user, and in
step 1205 the system generates and presents a draft report to a
physician or other qualified medical personnel for review. The
images may be reviewed by a user with the aid of a screen 320.
Next, in step 1206, after a reviewer edits or modifies the report,
the system compares the edits and reviews the images again to
determine whether the changes in the report are supported by
recognizable differences in the images or other deviations from the
standard images that represent the patient's original diagnosis.
The comparison in step 1206 can be made with the aid of a
processor. Then, in step 1207, diagnostic tables are updated for
future use, according to changes and differences found, and then in
step 1208 the procedure ends. The update in step 1207 can be made
using a processor.
[0124] FIG. 1300 shows an exemplary process 1300 for follow-up of
post-visit patient history, in accordance with another embodiment
of the invention. From time to time the system updates and collects
information from other databases, such as referring doctors,
hospitals, clinics, research data, etc. In step 1301, the follow-up
data is accessed or downloaded, typically over a network, and
analyzed. It is typically added to the repository, again, in this
example, repository 1021d, which may be any networked or otherwise
connected repository as described herein. In some situations, the
repository 1021d includes one or more physical storage mediums,
such as flash memory, random access memory and/or hard drives. The
repository 1021d may be a database operatively coupled to the
system, such as over an intranet or over the Internet (e.g., World
Wide Web).
[0125] Next, in step 1302, the newly obtained data or data sets are
analyzed for changes in diagnosis indicating a potential problem in
the previous diagnosis, or just a progression of the patient's
condition, for better or worse. In step 1303, the changes are
analyzed for resulting changes in prognosis. In step 1304, the
images are analyzed for additional clues differentiating at least
one of the previous images from the standard image(s) for the
initial diagnosis, allowing the system to refine its diagnosis
capabilities. In step 1305, the process splits into a "Manual" work
flow and an "Automatic" workflow. Moving to step 1307, the original
patient images, and in some cases reference images and analysis
tables, are updated automatically. Alternatively, moving to step
1306, with help of a physician or otherwise qualified personnel
performing an additional manual review on screen 320, the findings
proposed by the system are confirmed or corrected. When the
physician has reviewed the images, the information is updated in
step 1307 (as it was in case of only an automatic review) and the
procedure ends in step 1308. The purpose of this optional review is
to refine the analysis tables with follow up data of the actual
patients. The information is typically stored in a database that
has one or more tables (e.g., multiple tables), including a
standard object and deviation from the norm, and thus refine
continuously the system's decisions. There are many different
approaches according to which such additional data may influence
future diagnostic models, and different outcomes may translate to
better images analysis.
[0126] For example, the system may report "moderate" findings for a
case such as pleural effusion. In system analyses over time, the
same finding is reported over time for many patients as "severe."
The system then learns and adapts automatically the severity range
table. This effect is achieved by the system automatically updating
its lookup tables for the severity of findings based on its
quantitative measurements of each finding.
[0127] In another example, in a report a radiologist may use
different and/or additional key images to the key images
automatically reported by the system. The system then automatically
lears from these examples and corrects and adjusts its algorithms
accordingly for improved key image selection and/or gray scale
windowing.
Alerts to Various Participants
[0128] In another aspect of the invention, systems and methods are
provided for raising alerts for urgent medical conditions, whether
they were anticipated or not, and, based on those alerts, immediate
emergency response may be requested, or additional review by
another radiologist or other qualified personnel. The system may
also have a decision support system where additional clinical
findings can be checked to determine whether the alert should have
been raised or not, and added visualization that highlights the
items that led to the raising of the alert. Alerts provided to a
radiologist on duty and/or referring physician could be in the form
of an automatic phone call, short message service (SMS) text
message, multimedia messaging service (MMS) text message, or email
to which a summary of key critical findings may be attached to show
salient information, such as, for example, key images or
measurements. Additionally, the enhanced system and method
disclosed herein may prioritize a radiologist's work list by
leveraging CAD findings to analyze a patient's condition and
designate case priorities within the work list. Information from
enhanced analytics may be used create flags within the radiologist
work list, such as, for example, designating a case as high,
medium, or low priority. This information may also be used to
control the order of the cases in the work list such that a
higher-priority case is placed above a lower-priority case.
[0129] In some embodiments, a method for providing medical
diagnostic images comprises retrieving, using a processor, one or
more images from an image database or an imaging device, the one or
more images defining a set of images. One or more boundary
parameters are then obtained from a memory. Next, using a
processor, the system determines whether each of the images falls
within the boundary parameters. Next, one or more alerts for an
urgent medical condition are provided if one or more of the images
falls within the boundary parameters. The one or more alerts may be
raised to request an immediate emergency response.
[0130] In some embodiments, a system for providing medical
diagnostic images comprises an imaging modality for retrieving
medical diagnostic images from a patient; a database comprising one
or more boundary parameters; a processor configured to compare the
retrieved images with the one or more boundary parameters; and an
alert system in communication with the imaging modality and
database configured to provide one or more alert for an urgent
medical condition if one or more of the images falls within the
boundary parameters. In an embodiment, the boundary parameter is
the volume of air within a thorax or outside one or both lungs. In
another embodiment, the alert system is configured to provide the
one or more alert without intervention or review by a physician. In
another embodiment, the system further comprises a prioritizing,
visualization and reporting system (or sub-system) in communication
with the imaging modality and reviewing system, wherein the
prioritization, visualization and reporting system is configured
to: retrieve one or more images from the imaging modality, the one
or more images defining a set of images; and determine whether one
or more of the images is representative of the set of images and
provide the one or more images to the reviewing system, wherein the
one or more images are provided with an image that is
representative of the set of images.
[0131] FIG. 14a shows an exemplary process 1400 for the
implementation of an enhanced alert system, in accordance with an
embodiment of the invention. In step 1401a set of images is
received by the system from cloud 1002 from one of the other
processing elements as discussed herein. In some embodiments, the
set of images, which include one or more images, are retrieved with
the aid of a processor. The cloud 1002 may include one or more
computer systems operatively coupled to the system through the
Internet, an intranet, or both. In some cases, the process may
begin after only part of the set of images is received; in other
cases, the system may wait until all images are received, or it may
begin after receiving only part of the set, and then go through the
process again after receiving all the images in a set. In step 1402
a set of red-flag boundaries are retrieved from a database (also
"data base" herein), such as, for example, database (or data
repository) 1021d, the retrieval occurring at the end of a
request-and-response process 1403. In step 1404 the system compares
data from the processed images to the flag list parameters to
determine whether certain boundaries are exceeded, either minimally
or maximally. For example, if the volume of air in the thorax
outside one or both lungs, a condition known as pneumothorax,
exceeds a level determined by one of the parameters in the flag
list, there is an acute danger of the lung collapsing. Thus when
the ratio of the volume of air outside the lung to the overall
thorax, for example, goes below a certain boundary, the system sets
a red flag. In step 1405, the system checks for a red flag. If the
system finds a red flag ("yes"), the process moves to step 1406,
where the system retrieves patient information, including all
referring and specialist physicians involved in treatment. In step
1408 the system sends an alert 1409a-n to all discovered
physicians. These alerts may be automated telephone messages, pager
alerts, emails, text messages (e.g., SMS text messages, MMS text
messages), or any combination thereof, such as, for example, a
pager alert notifying the physician of an urgent email. If, in step
1405, the system does not find a red flag ("no"), and also after
step 1408, the process moves to step 1410, where additional
information about the patient's treatment history and any other
pertinent facts about the case may be retrieved from a database,
such as database 1021d or any other database or data repository. In
step 1411, the system sends the retrieved information, pictures
highlights, and links to more detailed information and pictures via
communication methods 1412a-n to all medical personnel involved in
the patient's treatment, which communication methods 1412a-n may be
similar to communication methods 1409a-n. In step 1413 the process
ends.
[0132] FIG. 14b shows an exemplary process 1420 for an optional
continuation from step 1411 of process 1400, in accordance with an
embodiment of the invention. In step 1421, the system retrieves the
priority list of the radiologist and the ER from database 1021d or
other database. This list may pertain to the treatment of the
particular patient who is the subject of the alert in process 1400
above, or be a general occasional rearrangement, or a combination
of both instances. In step 1422, the system gets priority rankings
from steps 1408 and 1411, described above. In step 1423, the system
likewise gets a triage priority list, again from database 1021d or
other data base. In step 1424 the system proposes a re-arranged
priority list to the ER and the radiologist. In step 1425 the
system receives approval from the physician or physicians in
charge, including but not limited to physicians in charge of the
ER, the radiologist, and, if applicable, a specific patient's
treatment. In step 1426 the system implements the rearranged
priorities list, and in step 1427 the process ends.
[0133] In some embodiments, systems and methods disclosed herein,
such as PACS systems or PAPVR systems, provide enhanced analytics
of medical diagnostic images based on the history of the patient
and comparable data, using preimposed historical data from the
patient, to further enhance analytics and then compare the
patient's current images to the patient's historic images, while
also comparing the images against peer group images and to the
outcome histories recorded in the analytical database ("DB") to
further improve analytics. This approach is based on smart
filtering that uses various methods as described throughout herein
to detect various medical conditions and to track a patient's
progress.
[0134] In some embodiments, methods for providing patient medical
diagnostic images comprise retrieving, using a processor, one or
more images associated with a patient from an image database or an
imaging device, the one or more images defining a set of images.
Next, historical data of the patient is retrieved from a memory.
Using a processor, the one or more images are compared with the
historical data. The one or more images and the historical data are
then provided to a reviewing physician.
[0135] In some embodiments, a system for providing medical
diagnostic images comprises an imaging modality for retrieving
medical diagnostic images from a patient; a database comprising
historical data of said patient; a processor configured to compare
the retrieved images with the historical data of said patient; and
a prioritizing, visualization and reporting system in communication
with the imaging modality and the database configured to provide
the images and the historical data to a reviewing physician.
[0136] In some situations, the system uses prior cases of same
patient and also brings similar cases from a knowledge base, rather
than from the same patient. A medical technician or other qualified
individual then identifies specific attributes in the current case
and uses those attributes to search a comprehensive medical data
base so that similar cases can be obtained to help a radiologist
diagnose the current case. More specifically, the system retrieves
relevant medical article on a subject disease and finds patient
comparables for statistical information on this subject disease
and/or patients. It then extracts time-dependent attributes
(comparisons of two or more time points, e.g., clinical
measurements, such as volume of pneumothorax); and it includes
attributes, measurements, statistics, examples from similar cases,
as well as relevant publications, in a preliminary report for a
radiologist to use in creating a final report to the referring
physician. The time dependent attributes may be extracted
periodically, such as at set intervals.
[0137] FIG. 15 shows an exemplary process 1500 for the
implementation of an enhanced analytics system, in accordance with
an embodiment of the invention. In step 1501 the system (e.g., PACS
system, PAPVR system) retrieves from a database, such as, for
example, database 1021d or any other database, a list of diseases
that it has previously diagnosed. In step 1502, the system
retrieves from the same database a list of approved sources and
previously retrieved articles. In step 1503, the system makes
searches, based on the lists generated in steps 1501 and 1502, of
its local database and of other sources throughout network 1002 and
Internet 1003, and retrieves new articles, diagnoses, image sets,
and other relevant data. In step 1504, the system retrieves
anonymous subject (e.g., patient) data available from local
databases, including diagnoses, history, etc. In step 1505 the
system processes and then, based on the diagnosed diseases or
conditions, as well as the physician's diagnosis of the patient
and/or the patient history, etc. ranks all the retrieved articles.
In step 1506 the system processes and adjusts the standards
according to peer groups; that is, the system sorts data in
multi-dimensional groups, according to such factors as patient age,
gender, life style and habits (e.g., whether the patient smokes,
whether the patient drinks excessively, whether the patient is
single or married), disease, progression and stage of disease, etc.
The system then uses this data to adjust standards for such
condition descriptors as "normal," "at risk," "critical," etc. for
patients in each group. The system may run process 1500 at a
predetermined time period, such as daily, weekly, monthly, or more,
which may be adequate to keep information up to date. The time
period balances the effort of processing all the data and the
latency in retrieving new data. In some cases, the time period is a
fixed time period (e.g., every week), while in other cases the time
period changes, such as, for example, from weekly to monthly or
vice versa.
[0138] FIG. 16 shows an exemplary process 1600 for the analysis of
patient medical data, in accordance with an embodiment of the
invention. In step 1601 the system receives a new set of patient
images for processing from network 1002. In step 1602 the system
retrieves previous data about this patient from database 1021d. In
step 1603 the system color codes (or uses other visual indicators)
the changes, dates, etc. if more than one historic snapshot is
available. In step 1604 the system sends the data to the patient's
physician for review, via, for example, the network 1002. In step
1605 the system determines whether the case is simple or complex,
based on analysis of retrieved articles and other data, plus peer
group data. Cases may be characterized as simple or complex, for
example, upon input from a reviewing physician, or via a machine
learning algorithm that learns the types of cases one or more
physicians consider simple and the types of cases one or more
physicians consider complex. If the case is deemed simple ("yes"),
the process ends at step 1606. If the case is not deemed simple
("no"), in step 1607 the system gets peer group data, as described
above in the discussion of step 1506 of FIG. 15, from database
1021d. In step 1608 the system matches the retrieved peer group
data against any new development in the case currently under
analysis. In step 1609 the system sends any additional relevant
information to the patient's physician, and then the process ends
at step 1606. In some cases, if, at step 1605, the system has
determined that the case is simple, the physician may request the
system to treat the case as complex and retrieve and match peer
group data. In other cases, the system is configured to treat all
cases as complex and always execute steps 1607-1609.
[0139] FIG. 17 shows two exemplary screens of various systems and
methods disclosed herein. Screen 1700 is an application management
screen, and screen 1710 is an application store screen. The screens
may be part of a graphical user interface (GUI) of a system (e.g.,
PACS system, PAPVR system). The GUI may be stored in a machine
readable medium (e.g., flash memory, cache, hard disk) and
implemented by a processor of the system. The GUI may be part of an
operating system or a software component of the system. A mode
control area 1705 in screen 1700 shows the current mode of the
system, and whether it is an approved or non-approved mode. A user
may click on a button in area 1705 to toggle a mode on or off, or
select a different mode from a list. One mode is typically
specified as a default mode. In an example, in the United States,
typically, the default mode may be an FDA-approved mode. In this
mode, only FDA-approved modules and plug-ins are used. Any
activation of other, non-approved modules automatically takes the
system out of the default FDA-approved mode. The system in such a
case provides a user a visual non-default mode indicator, such as,
for example, a red blinking frame around the system screen display
(see above), resulting in an overlay imprint on any images, films,
etc., which renders certain modules and plug-ins non-approved for
patient use. Screen 1700 also includes an application overview
section 1701, with a header section 1702. Columns 1703a-n show the
various modes and applications in the system and information about
each app, such as their state (i.e., whether active or inactive),
revision level, date downloaded, price, etc.
[0140] Display of some features of the application management
screen may be blocked or modified by a system management console
(not shown) that only a system administrator can control. In an
example, only the administrator (or other user with the requisite
privileges) is able to change the default mode; users, such as
physicians, are not able to change the default mode. Clicking on
button 1704 transfers the display to application store screen 1710,
where a user can review and select various available applications
and plug-ins. In screen 1710, a header section 1711 shows the
system identification and has a field in which a user can enter
search terms for application ("app") store (e.g., Apple.RTM. App
store) products. Additional search criteria are shown in section
1712, such as, for example, limitation to programs with certain
types of approvals, or limitation to specific medical fields, such
as lungs, ear-nose-throat, brain, etc. Section 1713 displays the
results returned from a search in lines 1714a-n and selection check
boxes 1715a-n. A user may check a box to add a product to an
electronic "shopping cart". When the user has made all desired
selections, he may then click on button 1716 to activate the
purchase and initiate the download.
[0141] FIG. 18 shows an exemplary process 1800 for user interaction
with app store modules, in accordance with an embodiment of the
invention. In step 1801, the application management module 1700 is
launched. In step 1802, the screen is displayed and the user may
begin the user's interaction with the system. In step 1803, the
user makes a selection, after which one of various system modules
may be launched. In selection 1804, the user has elected to
activate certain previously inactive applications. If these
applications include a non-approved application (e.g., a non-FDA
approved application), an additional warning may appear on the
screen, and then the mode, as shown, for example, in mode control
area 1705, described above, may change to a non-approved mode. In
selection 1805 the user may elect to change the application mode
directly. This deliberate change of mode may result in certain
applications becoming inactive if, for example, the user changes
from a non-approved mode to an approved mode while certain
non-approved applications are active. In selection 1806, the user
has elected to add new apps to the system by clicking on button
1704, as described above. In step 1807, the system launches the app
store 1710, and in step 1808 the user searches for apps that meet
the user's specified criteria. The user then selects one or more
products from the returned search results. In step 1809 payment is
arranged, using any of various payment methods available for online
stores, such as, for example, giving the system credit card
information, or a billing arrangement with the system operator, or
any other of many available payment options. In step 1810 the
selected products are downloaded and installed. The selected
products are then made available in application management screen
1800 for selection and activation.
[0142] FIG. 19 shows an overview of an exemplary app store
environment 1900, in accordance with an embodiment of the
invention. The app store is connected to Internet 1901, which may
be as described herein. Server 1910 has one or more software
instances 1911a-n, including but not limited to operating system,
web server, database, and other standard computer software, as well
as the app store application, to be described in greater detail
below. Storage unit 1920 contains various instances of data and
software, including apps, plug-ins, and other merchandise 1921a-n
for the store. In some cases, when server 1910 is not powered on,
the storage unit 1920 includes software instances 1911a-n. Rather
than a physical server 1910 and a physical storage unit 1920, the
app store environment may comprise virtual machines and/or cloud
services.
[0143] FIG. 20 shows an exemplary process 2000 for app store
transactions, in accordance with an embodiment of the invention. In
step 2001, a user visits an app store. In step 2002, the user or
the application selects the nature of the visit, such as a buyer's
initial visit, a buyer's return visit, or a developer's visit to
sell software. In some cases an application may interact directly,
hiding the store, while in other cases, a web browser may be used,
for example, for a developer to sell and upload software. If this
is a buyer's initial visit, the process moves to step 2003, where
the buyer sets up an account and is given the opportunity to review
and accept one or more buying agreements, one or more of which
agreements may specify one or more different types of regulatory
approvals, as described below. In step 2004 the app store and the
buyer's account exchange credentials to enable the store to verify
the buyer's identity upon revisits. Upon the buyer's subsequent
visit, the app store may require additional agreements to update,
for example, verification of the buyer's identity or because of
changes in the policies and merchandise of the store, changes in
regulations governing the products and services, etc. In step 2005,
the buyer, whether a first-time visitor or a return visitor, logs
in with his verified credentials. In step 2006 the app store
retrieves a list (e.g., by downloading the list) of available
merchandise, and in step 2007 the user selects items from the list.
Next, in step 2008 the buyer pays for his selected merchandise,
using, for example, a built-in payment system, a third-party
payment system, or some other available system for payment. In step
2009 the buyer downloads his merchandise and the transaction is
finished.
[0144] At step 2002, if a buyer is revisiting the store, the system
bypasses steps 2003 and 2004. The buyer is given the opportunity to
login at step 2005.
[0145] In the case of a seller's visit to list merchandise for sale
in the store, in step 2010 the seller sets up an account and in
step 2011 the seller is given the opportunity to review and accept
one or more agreements. When selling an item, a seller must decide
what rights to give the buyer. For example, if a seller is selling
a model, for example, of a typical disease appearance, or for
boundary values, etc., rather than a software instance, the seller
may give the buyer permission to use the model for the buyer's own
purpose and/or within the buyer's organization, but in some cases
the buyer does not have the right to distribute the model to any
person or entity outside the buyer's organization unless he
purchases some additional rights and licenses. In some cases, there
may be additional restrictions associated with the buyer's
permission to use the model. In some cases, the store may present a
multi-level (with each level providing certain rights) agreement,
and the seller may select the level of rights he is willing to
sell. In step 2012, the store and the seller exchange and/or verify
credentials. This exchange of credentials may be required upon each
visit by a seller, even repeat visits, because each new instance of
merchandise may require approval by a regulatory body (e.g., the
FDA), and in such cases the seller is responsible for obtaining the
required approvals. In some situations, credentials that verify the
seller's machine may not be adequate; rather, the actual personal
identity of the seller who vouches for regulatory compliance must
be verified. In step 2013 the seller selects the desired pricing
and rights for this particular merchandise from a multi-level
agreement, as described above, or the seller may request additional
pricing and rights agreements. In step 2014 the seller (or a
computer system of or associated with the seller) uploads the
seller's merchandise, and in step 2015 the transaction ends. The
seller may receive payments for the merchandise by any payment
system, which could be a proprietary payment system or a public
system, such as credit card account, PayPal.RTM., wire transfer, or
credits (e.g., store credits).
[0146] Various modifications and variations of systems and methods
disclosed herein may be made by one skilled in the art without
departing from the spirit of the invention. For example, the system
may retrieve one or more medical diagnostic images from an image
database and use algorithms and rules to determine whether any of
the images are of medical interest to a reviewing physician, and
use tables to determine whether any one image should be part of a
set of images. The system may then send the set of images to a
display and analysis system for review by a physician or other
qualified reviewer, who may, after reviewing the images, update the
tables. Further, the system may track a patient's outcome by
continuously following the initial findings and the responsiveness
to treatment, and updating the tables accordingly. Additionally,
the system may track the patient's clinical diagnosis and compare
that with the initial radiological findings and then follow up in
clinical treatment up to full resolution of the problem to
determine whether the initial findings were supported or not, and
if not, assessing any discrepancies and subsequently updating the
tables with the discrepancy-related information or missing
information, if any. Also, in tracking patient outcome, the
diagnostics can be further enhanced and refined over time, thus
improving the results by using machine learning at two levels, the
first level involving looking at a final report by a radiologist
and comparing it to the system's preliminary report, which may be
automatically generated, and the second level involving
adjusting/refining algorithms to match (or conform to) the
radiologist's report.
[0147] For example, systems (e.g., PACS system, PAPVR system) and
methods described herein may retrieve patient medical diagnostic
images from an image database and then compare the current data to
historical data of the patient. Further, based on the history of
the patient and comparable data, the system may use preimposed
historical data from the patient to further enhance analytics. The
system may then compare initial findings to outcomes recorded in
historical data, and make that additional finding available to a
physician. Also, the system may use its findings to further improve
analytics for future cases, using smart or targeted filtering that
uses various methods described herein to detect various medical
situations. Additionally, the diagnostic system may be used to
identify specific attributes in the current case and then use those
attributes to search a depository of medical data so that similar
cases can be obtained to help a radiologist diagnose the current
case. The system may provide relevant medical articles on the
diagnosed disease or condition, and it may extracts time-dependent
attributes (such as comparisons of two or more time points, e.g.,
clinical measurements, such as volume of pneumothorax). All such
data may be made available to an operator; such available data may
include, without limitation, volume, attributes, measurements,
statistics, examples from similar cases, as well as relevant
publications in a preliminary report for a radiologist to use in
creating a final report to the referring physician.
[0148] In some embodiments, a method for providing medical
diagnostics comprises providing access to one or more platforms
("platform") capable of distributing one or more applications
configured to implement a method comprising retrieving, using a
processor, one or more images from an image database or an imaging
device, the one or more images defining a set of images;
determining, using a processor, whether each of the images is of
medical interest to a reviewing physician; providing one or more
images to a display and analysis system for review by a reviewing
physician, wherein the one or more images are provided with an
image that is representative of the set of images. The platform may
be a computer system having the processor among one or a plurality
of processors.
[0149] In an embodiment, the platform receives a selection by a
user for one or more of the applications accessible by the
platform, and provides the one or more selected applications to the
user. In another embodiment, the platform receives one or more
search parameters from the user and provides the user an option for
one or more applications that meet the one or more search
parameters. The user may elect the option provided by the computer
system. The one or more selected applications, in some cases, are
provided to the user on a per use or subscription model (or
basis).
[0150] The platform may permit one or more developers to download
or purchase one or more APIs and/or SDKs. In some cases, the
platform may provide a test mode capable of receiving a clinical
data set to test one or more selected application. In some cases,
if the test is successful, a protocol is provided to submit and
clear the application. In some situations, the platform indicates
whether the one or more applications are FDA approved, are in
process for FDA approval, or have another status.
[0151] In some embodiments, a system for providing medical
diagnostics comprises one or more platforms ("platform") capable of
distributing one or more applications configured to implement a
method comprising retrieving, using a processor, one or more images
from an image database or an imaging device, the one or more images
defining a set of images; determining, using a processor, whether
each of the images is of medical interest to a reviewing physician;
and providing one or more images to a display and analysis system
for review by a reviewing physician, wherein the one or more images
are provided with an image that is representative of the set of
images. The system further comprises an interface, such as a
graphical user interface (GUI), configured to receive one or more
user input related to the distribution of the one or more
applications.
[0152] In some cases, a platform for evaluating and distributing
apps to provide enhanced analytics, alerts, notifications, etc.,
through an app store may be made available, where customers can
search for applications ("apps") of interest and buy selected apps
on a per-use, one-time license fee, or subscription model. Further,
for third-party developers, the platform may provide an application
programming interface (API), software development kit (SDK), and
test mode in which it provides clinical data to test the app, and
if successful, provides a protocol to submit and clear the app
through a regulatory body (e.g., FDA), if required. In addition,
the app store may have a categorization and a smart filtering
system to enable customers to view the statuses (e.g., approved,
denied) of applications and, in some cases, view approved
applications, and review informal ideas shared by other
professionals without requiring the user to do manual verification.
For example, the app store shows customers whether an app is FDA
approved, in process, or not in process.
[0153] Systems and methods of the disclosure may be combined with
or modified by other systems and methods, such as those described
in PCT/US2011/023059 ("METHODS AND SYSTEMS FOR ANALYZING,
PRIORITIZING, VISUALIZING, AND REPORTING MEDICAL IMAGES"), which is
entirely incorporated herein by reference.
[0154] These modifications and variations do not depart from its
broader spirit and scope, and the examples cited here are to be
regarded in an illustrative rather than a restrictive sense.
[0155] It should be understood from the foregoing that, while
particular implementations have been illustrated and described,
various modifications can be made thereto and are contemplated
herein. It is also not intended that the invention be limited by
the specific examples provided within the specification. While the
invention has been described with reference to the aforementioned
specification, the descriptions and illustrations of the preferable
embodiments herein are not meant to be construed in a limiting
sense. Furthermore, it shall be understood that all aspects of the
invention are not limited to the specific depictions,
configurations or relative proportions set forth herein which
depend upon a variety of conditions and variables. Various
modifications in form and detail of the embodiments of the
invention will be apparent to a person skilled in the art. It is
therefore contemplated that the invention shall also cover any such
modifications, variations and equivalents. It is intended that the
following claims define the scope of the invention and that methods
and structures within the scope of these claims and their
equivalents be covered thereby.
* * * * *